ConnectOne Bank Achieves 50% Efficiency Gains in Commercial Lending with nCino AI

nCino agentic AI is an embedded artificial intelligence system within the nCino banking platform that enables automation of administrative tasks in commercial lending through knowledge bases and custom agents.

Executive Summary

ConnectOne Bank, operating as ConnectOne Bancorp, Inc., maintains approximately $14 billion in assets across 57 branches in New York, New Jersey, and Long Island. The institution began deploying nCino's embedded AI capabilities in its commercial lending operations in April 2026. These capabilities target routine administrative tasks that previously required substantial time from frontline staff.

The specific AI components include the Banking Advisor Knowledge Base for rapid document retrieval and custom agents built on Document Intelligence for relationship data updates. Initial measurements show document search times falling from 20 minutes to as little as 30 seconds. A separate custom agent delivered a 60 percent reduction in time for updating individual and business relationships.

The bank anticipates a 50 percent efficiency gain for frontline bankers. This projection equates to 1,000 hours per banker freed annually for higher-value work. ConnectOne has maintained a nCino relationship since 2017 and holds a top 1 percent national ranking for efficiency.

Background and Context

ConnectOne Bank established its nCino partnership in 2017 to support scaling while preserving an efficient operating model. The bank required tools that could accelerate speed to market in commercial lending. Prior to the 2026 AI additions, the platform handled core functions but left manual administrative burdens in place for policy searches and data maintenance.

Commercial lending at the bank involves frequent reference to credit policies and job aids. Bankers historically allocated up to 20 minutes per search across documentation. These tasks occurred daily and accumulated into significant non-revenue-generating time across the organization with its $14 billion asset base.

The institution's top 1 percent efficiency ranking provided a strong baseline. Executives identified opportunities to apply emerging AI features without disrupting established processes. The multi-state branch network benefits from centralized platform enhancements that maintain consistency across locations.

Sector pressures in banking include demands for productivity improvements amid regulatory requirements. ConnectOne's strategy emphasizes augmentation of existing staff capabilities rather than headcount changes. This approach aligns with the bank's long-standing focus on operational excellence.

What's New in Detail

The April 2026 deployment marked the introduction of nCino's agentic AI features into ConnectOne's commercial lending workflows. The Banking Advisor Knowledge Base provides instant access to policy documents and job aids that previously required extended manual searches. This change directly addresses the 20-minute task duration reported prior to implementation.

Custom agents were configured for targeted use cases. One agent applies Document Intelligence to automate updates to individual and business relationship records. The bank observed a 60 percent reduction in completion time for this workflow following agent activation.

User adoption metrics indicate rapid uptake. Active users of the Banking Advisor capability increased 41 percent within the first 10 weeks. This growth occurred across the frontline banking team responsible for commercial lending activities.

The deployment builds directly on the existing nCino platform in use since 2017. No separate infrastructure was required for the AI components. The changes allow bankers to shift focus from retrieval and data entry to client-facing and decision-oriented activities.

Technical Specifics

The Banking Advisor Knowledge Base functions as an integrated search layer over credit policy and job aid content. Queries that once required 20 minutes of navigation now resolve in as little as 30 seconds. Both nCino, Inc. and American Banker documented this time reduction in their coverage of the ConnectOne implementation.

The Document Intelligence agent processes incoming documents to extract and apply updates to relationship profiles. This automation eliminated manual entry steps that previously extended task duration. The 60 percent time savings on relationship updates was measured during the pilot phase.

Agentic capabilities operate within the parameters set by the bank's existing nCino configuration. The system handles defined queries autonomously while escalating complex cases to human review. Integration maintained continuity with the 2017-era platform foundation.

Deployment occurred without reported operational interruptions. Training and rollout supported the 41 percent user growth in 10 weeks. The technical approach leverages the platform's embedded nature to minimize change management overhead.

Measured Outcomes and Efficiency Gains

Document search time dropped from 20 minutes to as little as 30 seconds, representing a 97.5 percent reduction. This metric was confirmed in the nCino, Inc. announcement and American Banker reporting. The change applies to credit policy and job aid documentation searches.

The relationship update task achieved a 60 percent time reduction through the custom Document Intelligence agent. Combined with the search improvements, these gains contribute to the overall efficiency target. Active user growth of 41 percent in 10 weeks provides supporting evidence of operational impact.

The 50 percent efficiency projection originates from executive statements tied to the nCino collaboration. This figure translates directly to the 1,000-hour annual reclamation per banker. FinTech Global also referenced the time savings in its coverage of AI returns in banking.

Market and Stakeholder Implications

C-suite leaders in banking can examine the ConnectOne results as a benchmark for administrative task automation in commercial lending. The quantified reductions in search and update times offer concrete data points for similar environments. The approach demonstrates use of embedded AI within an established platform rather than standalone tools.

Stakeholders may note the emphasis on productivity augmentation. The CEO statements address whether efficiency gains lead to staffing reductions or output increases. This framing provides a model for internal discussions on AI deployment strategy.

Peer institutions with comparable lending volumes can reference the 97.5 percent search time reduction and 60 percent relationship task improvement. The 41 percent user adoption rate within 10 weeks supplies an additional adoption metric. ConnectOne's top 1 percent efficiency ranking adds context for the scale of the observed gains.

Before and After Comparison of Administrative Task Times at ConnectOne Bank

Task	Before AI	After AI	Reduction	Source
Document search for credit policy and job aids	20 minutes	30 seconds	97.5%	nCino, Inc.
Updating individual and business relationships	Baseline time	60% of baseline time	60%	nCino, Inc.
Frontline banker administrative load	Full baseline hours	50% efficiency gain projected	50%	nCino, Inc.

The multi-branch structure across three states benefits from centralized AI features that standardize task execution. Investors and regulators may view the measurable outcomes as indicators of operational discipline. The seven-year nCino relationship facilitated incremental feature adoption.

Expert Reactions

Chairman and CEO Frank Sorrentino III outlined the strategic intent behind the deployment. His comments focus on the potential to elevate every frontline banker by 50 percent through removal of low-value administrative work. The statements appear in both the nCino, Inc. release and American Banker coverage.

We are one of the most efficient banks in the country. I believe with the things we're working on today together with nCino, we are going to be able to make every single one of our frontline people 50 percent more efficient. Fifty percent means our bankers will work a thousand hours less on things that don't matter and a thousand hours more on the things that do.Frank Sorrentino III, Chairman and CEO, ConnectOne Bank

A second statement from Sorrentino addresses the productivity question directly. He notes the average banker works 2,000 hours annually and questions whether reclaimed time results in reduced headcount or doubled output. This perspective appears in the American Banker article.

The executive commentary aligns with the observed metrics including the 41 percent user growth and specific task reductions. Industry observers may interpret the rapid adoption as validation of the tool design within the existing platform. The quotes provide primary attribution for the 50 percent and 1,000-hour projections.

What's Next

ConnectOne Bank plans continued collaboration with nCino on expansion of agentic capabilities. Initial pilot results from the Banking Advisor and custom agents inform decisions on additional workflow coverage. The bank seeks to sustain its efficiency leadership position through ongoing platform enhancements.

Future agent development may target other document-intensive processes in commercial lending. The existing integration since 2017 supports iterative additions without platform replacement. The 41 percent user growth provides a foundation for scaling across the 57-branch network.

Other banks evaluating similar deployments can reference the documented time reductions and adoption rates. The case illustrates benefits from long-term vendor relationships in achieving incremental AI integration. ConnectOne's top 1 percent efficiency baseline offers a reference point for expected outcomes.

1. Review current administrative time allocation in commercial lending document and relationship tasks.
2. Identify pilot workflows for embedded AI knowledge base and Document Intelligence agents.
3. Track time reductions, user adoption, and productivity shifts over an initial 10-week period.
4. Assess strategic allocation of reclaimed hours toward client-facing or revenue activities.
5. Expand validated agents to additional processes based on measured results and user feedback.

The ordered considerations reflect the sequence observed in the ConnectOne deployment. Executives at peer institutions may adapt these steps to their operational contexts. Continued reporting from nCino and American Banker will provide updates on further outcomes.